research
∙
07/05/2023
Open-Domain Hierarchical Event Schema Induction by Incremental Prompting and Verification
Event schemas are a form of world knowledge about the typical progressio...
share
research
∙
07/04/2023
ReactIE: Enhancing Chemical Reaction Extraction with Weak Supervision
Structured chemical reaction information plays a vital role for chemists...
research
∙
06/24/2023
Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers
Instead of relying on human-annotated training samples to build a classi...
research
∙
06/16/2023
Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation From Deductive, Inductive and Abductive Views
Large Language Models (LLMs) have achieved great success in various natu...
research
∙
06/05/2023
Explaining and Adapting Graph Conditional Shift
Graph Neural Networks (GNNs) have shown remarkable performance on graph-...
research
∙
05/24/2023
Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models
The mission of open knowledge graph (KG) completion is to draw new findi...
research
∙
05/23/2023
Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation
Instruction tuning has emerged to enhance the capabilities of large lang...
research
∙
05/21/2023
OntoType: Ontology-Guided Zero-Shot Fine-Grained Entity Typing with Weak Supervision from Pre-Trained Language Models
Fine-grained entity typing (FET), which assigns entities in text with co...
research
∙
05/20/2023
Patton: Language Model Pretraining on Text-Rich Networks
A real-world text corpus sometimes comprises not only text documents but...
research
∙
04/08/2023
Unsupervised Story Discovery from Continuous News Streams via Scalable Thematic Embedding
Unsupervised discovery of stories with correlated news articles in real-...
research
∙
04/04/2023
MEGClass: Text Classification with Extremely Weak Supervision via Mutually-Enhancing Text Granularities
Text classification typically requires a substantial amount of human-ann...
research
∙
03/16/2023
GLEN: General-Purpose Event Detection for Thousands of Types
The development of event extraction systems has been hindered by the abs...
research
∙
02/21/2023
Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks
Edges in many real-world social/information networks are associated with...
research
∙
02/10/2023
PDSum: Prototype-driven Continuous Summarization of Evolving Multi-document Sets Stream
Summarizing text-rich documents has been long studied in the literature,...
research
∙
02/07/2023
Augmenting Zero-Shot Dense Retrievers with Plug-in Mixture-of-Memories
In this paper we improve the zero-shot generalization ability of languag...
research
∙
02/07/2023
The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study
Due to the exponential growth of scientific publications on the Web, the...
research
∙
02/04/2023
Representation Deficiency in Masked Language Modeling
Masked Language Modeling (MLM) has been one of the most prominent approa...
research
∙
12/12/2022
Effective Seed-Guided Topic Discovery by Integrating Multiple Types of Contexts
Instead of mining coherent topics from a given text corpus in a complete...
research
∙
12/05/2022
Entity Set Co-Expansion in StackOverflow
Given a few seed entities of a certain type (e.g., Software or Programmi...
research
∙
11/30/2022
Open Relation and Event Type Discovery with Type Abstraction
Conventional closed-world information extraction (IE) approaches rely on...
research
∙
11/06/2022
Tuning Language Models as Training Data Generators for Augmentation-Enhanced Few-Shot Learning
Recent studies have revealed the intriguing few-shot learning ability of...
research
∙
11/03/2022
Open-Vocabulary Argument Role Prediction for Event Extraction
The argument role in event extraction refers to the relation between an ...
research
∙
10/20/2022
Large Language Models Can Self-Improve
Large Language Models (LLMs) have achieved excellent performances in var...
research
∙
09/29/2022
Few-shot Text Classification with Dual Contrastive Consistency
In this paper, we explore how to utilize pre-trained language model to p...
research
∙
09/15/2022
TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations
We present TwHIN-BERT, a multilingual language model trained on in-domai...
research
∙
08/21/2022
MentorGNN: Deriving Curriculum for Pre-Training GNNs
Graph pre-training strategies have been attracting a surge of attention ...
research
∙
06/28/2022
Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance Generation
We study the problem of few-shot Fine-grained Entity Typing (FET), where...
research
∙
06/15/2022
TeKo: Text-Rich Graph Neural Networks with External Knowledge
Graph Neural Networks (GNNs) have gained great popularity in tackling va...
research
∙
06/06/2022
Schema-Guided Event Graph Completion
We tackle a new task, event graph completion, which aims to predict miss...
research
∙
05/22/2022
All Birds with One Stone: Multi-task Text Classification for Efficient Inference with One Forward Pass
Multi-Task Learning (MTL) models have shown their robustness, effectiven...
research
∙
05/20/2022
Heterformer: A Transformer Architecture for Node Representation Learning on Heterogeneous Text-Rich Networks
We study node representation learning on heterogeneous text-rich network...
research
∙
05/12/2022
CiteSum: Citation Text-guided Scientific Extreme Summarization and Low-resource Domain Adaptation
Scientific extreme summarization (TLDR) aims to form ultra-short summari...
research
∙
05/04/2022
Seed-Guided Topic Discovery with Out-of-Vocabulary Seeds
Discovering latent topics from text corpora has been studied for decades...
research
∙
04/29/2022
OA-Mine: Open-World Attribute Mining for E-Commerce Products with Weak Supervision
Automatic extraction of product attributes from their textual descriptio...
research
∙
04/07/2022
Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators
We present a new framework AMOS that pretrains text encoders with an Adv...
research
∙
02/15/2022
PILED: An Identify-and-Localize Framework for Few-Shot Event Detection
Practical applications of event extraction systems have long been hinder...
research
∙
02/11/2022
Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification
Large-scale multi-label text classification (LMTC) aims to associate a d...
research
∙
02/10/2022
TaxoEnrich: Self-Supervised Taxonomy Completion via Structure-Semantic Representations
Taxonomies are fundamental to many real-world applications in various do...
research
∙
02/09/2022
Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations
Topic models have been the prominent tools for automatic topic discovery...
research
∙
02/09/2022
Generating Training Data with Language Models: Towards Zero-Shot Language Understanding
Pretrained language models (PLMs) have demonstrated remarkable performan...
research
∙
11/24/2021
Out-of-Category Document Identification Using Target-Category Names as Weak Supervision
Identifying outlier documents, whose content is different from the major...
research
∙
11/07/2021
MotifClass: Weakly Supervised Text Classification with Higher-order Metadata Information
We study the problem of weakly supervised text classification, which aim...
research
∙
10/17/2021
Fine-Grained Opinion Summarization with Minimal Supervision
Opinion summarization aims to profile a target by extracting opinions fr...
research
∙
10/14/2021
UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning
Conventional fine-tuning of pre-trained language models tunes all model ...
research
∙
09/26/2021
Entity Linking Meets Deep Learning: Techniques and Solutions
Entity linking (EL) is the process of linking entity mentions appearing ...
research
∙
09/21/2021
Chemical-Reaction-Aware Molecule Representation Learning
Molecule representation learning (MRL) methods aim to embed molecules in...
research
∙
09/10/2021
Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training
We study the problem of training named entity recognition (NER) models u...
research
∙
08/02/2021
Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data
There has been a recent surge of interest in designing Graph Neural Netw...
research
∙
06/17/2021
Multi-head or Single-head? An Empirical Comparison for Transformer Training
Multi-head attention plays a crucial role in the recent success of Trans...
research
∙
05/28/2021
